Table of Contents

Abstract: Remarkable developments can be seen in the field of optical fibre biosensors in the last decade. More sensors for specific analytes have been reported, novel sensing chemistries or transduction principles have been introduced, and applications in various analytical fields have been realised. This review consists of papers mainly reported in the last decade and presents about applications of optical fiber biosensors. Discussions on the trends in optical fiber biosensor applications in real samples are enumerated.

Abstract: Three operative models with minimum input data requirements for estimatingthe partition of available surface energy into sensible and latent heat flux using ASTERdata have been evaluated in a semiarid area in SE Spain. The non-evaporative fraction(NEF) is proposed as an indicator of the surface water deficit. The best results wereachieved with NEF estimated using the “Simplified relationship” for unstable conditions(NEF_Seguin) and with the S-SEBI (Simplified Surface Energy Balance Index) modelcorrected for atmospheric conditions (NEF_S-SEBIt,) which both produced equivalent results.However, results with a third model, NEF_Carlson, that estimates the exchange coefficient forsensible heat transfer from NDVI, were unrealistic for sites with scarce vegetation cover.These results are very promising for an operative monitoring of the surface water deficit,as validation with field data shows reasonable errors, within those reported in the literature(RMSE were 0.18 and 0.11 for the NEF, and 29.12 Wm^-2 and 25.97 Wm^-2 for sensible heatflux, with the Seguin and S-SEBIt models, respectively).

Abstract: A comparison of chlorophyll data from SeaWiFS imagery and modeling results from a 3D hydrodynamical model was performed over the northwestern Mediterranean for the entire year of 2001. The study aims at investigating the information content brought by satellite-derived chlorophyll concentration ([Chl]) maps concerning surface dynamics in coastal zone. The study is mainly focused on the Gulf of Lions (GoL) and its outer region, which are mainly influenced by the Rhône River, local winds and the Northern Current (NC) flowing from the East along the continental slope. The physical hydrodynamical model was continuously run and 40 SeaWiFS images, presenting a significant coverage of the studied area, were selected. The comparison between [Chl] and sea surface salinity (SSS) fields on a pixel basis showed no definite correlation trends. Three reasons are given in discussion for that result. However, the comparison emphasized areas close to the coasts which were under the influence of different inputs not considered in the model and also of upwellings. A qualitative analysis of the data performed out of these regions exhibited significant similarities between [Chl] and SSS features. The signature of the Rhône ROFI (Region of Fresh Water Influence) and, in some cases, of the NC, was evidenced on [Chl] maps. We found that the intensity of this signature is seasonally modulated, e.g., it is low in open sea during the summer, oligotrophic, season. In addition, the signature of the Rhône ROFI in the western part of the GoL can be only partial due to local chlorophyll deficits. We conclude that, for the regional case studied, chlorophyll imagery can be used as a tracer of surface dynamics through surface salinity but with limitations, especially near the coasts.

Abstract: This paper presents a nonlinear Bayesian regression algorithm for detecting and estimating gas plume content from hyper-spectral data. Remote sensing data, by its very nature, is collected under less controlled conditions than laboratory data. As a result, the physics-based model that is used to describe the relationship between the observed remote- sensing spectra, and the terrestrial (or atmospheric) parameters that are estimated is typically littered with many unknown ”nuisance” parameters. Bayesian methods are well-suited for this context as they automatically incorporate the uncertainties associated with all nuisance parameters into the error estimates of the parameters of interest. The nonlinear Bayesian re- gression methodology is illustrated on simulated data from a three-layer model for longwave infrared (LWIR) measurements from a passive instrument. The generated LWIR scenes con- tain plumes of varying intensities, and this allows estimation uncertainty and probability of detection to be quantified. The results show that this approach should permit more accurate estimation as well as a more reasonable description of estimate uncertainty. Specifically, the methodology produces a standard error that is more realistic than that produced by matched filter estimation.

Abstract: An intelligent textile is a textile structure that measures and reacts in front of external agents or stimulus with or without integrated electronic equipment. . The finality of the present textile is to take one more step towards intelligent textile, considering the integration of electronics and textile needs, to be industrially viable and to keep up the necessary competitiveness, raising the final price as little as possible. The finality of these experiments is to develop a textile that varies in conductivity and resistance in relation to the elongation of the textile, detecting changes caused by the alteration of a piece of clothing, from the pressure of a finger on the material, for example. One of the most important characteristics of textile is the capacity of reproducing measures, of varying the response in different tests. Two lines of research were opened: the study of the most adequate structure to achieve a response that can be reproduced and the study of the best way of taking measures without altering the behavior of the textile.

Abstract: Due to unique physico-chemical properties of –SH moiety thiols comprise widegroup of biologically important compounds. A review devoted to biological functions ofglutathione and phytochelatins with literature survey of methods used to analysis of thesecompounds and their interactions with cadmium(II) ions and Murashige-Skoog medium ispresented. For these purposes electrochemical techniques are used. Moreover, we revealedthe effect of three different cadmium concentrations (0, 10 and 100 μM) on cadmiumuptake and thiols content in maize plants during 192 hours long experiments usingdifferential pulse anodic stripping voltammetry to detect cadmium(II) ions and highperformance liquid chromatography with electrochemical detection to determineglutathione. Cadmium concentration determined in tissues of the plants cultivated innutrient solution containing 10 μM Cd was very low up to 96 hours long exposition andthen the concentration of Cd markedly increased. On the contrary, the addition of 100 μMCd caused an immediate sharp increase in all maize plant parts to 96 hours Cd expositionbut subsequently the Cd concentration increased more slowly. A high performance liquidchromatography with electrochemical detection was used for glutathione determination intreated maize plants after 96 and 192 hours of treatment. The highest total content of glutathione per one plant was 6 μg (96 h, 10 μM Cd) in comparison with non-treated plant (control) where glutathione content was 1.5 μg. It can be concluded that electrochemical techniques have proved to be useful to analyse plant thiols.

Abstract: Previous brain electrophysiological research has studied the interregionalconnectivity during the tapping task and found that inter-hemispheric alpha coherence wasmore significant under bimanual task conditions than that under unilateral conditions, butthe interregional connectivity situation in the unilateral tapping condition was not exploredclearly. We have designed a unilateral repetitive finger-tapping task to delineate the anteriorand posterior cortex contributions to unilateral finger movement. Sixteen right handedcollege students participated in this study. Event related potentials (ERPs) and the strengthof event related coherence (ERCoh) were analyzed to examine the antero-posterodominance of cortical activity in the phase of early visual process (75-120ms), pre-execution(175-260ms), execution (310-420ms) and post-execution (420-620ms). Results showed thatthe occipital (Oz, O1 and O2), frontal (Fz, F3, and F4), fronto-central (Fz, Cz, F3 and C3),and parietal regions were the most pronounced in the early visual, pre-execution, execution,and post-execution phases, respectively. Moreover, among four inter-hemispheric pairs onlythe Coh (C3 and C4) was significantly correlated to reaction time (RT) of tapping in theexecution phase. In conclusion, the aforementioned variability of electrophysiological data(ERPs and coherence) and the change of antero-postero regional dominance with timereflect the relative importance of different mechanisms in different phases. The mechanismsof visual processing, motor planning, motor execution and feedback reward wereoperational, respectively.

Abstract: Accurate crop performance monitoring and production estimation are critical fortimely assessment of the food balance of several countries in the world. Since 2001, theFamine Early Warning Systems Network (FEWS NET) has been monitoring cropperformance and relative production using satellite-derived data and simulation models inAfrica, Central America, and Afghanistan where ground-based monitoring is limitedbecause of a scarcity of weather stations. The commonly used crop monitoring models arebased on a crop water-balance algorithm with inputs from satellite-derived rainfallestimates. These models are useful to monitor rainfed agriculture, but they are ineffectivefor irrigated areas. This study focused on Afghanistan, where over 80 percent ofagricultural production comes from irrigated lands. We developed and implemented aSimplified Surface Energy Balance (SSEB) model to monitor and assess the performanceof irrigated agriculture in Afghanistan using a combination of 1-km thermal data and 250-m Normalized Difference Vegetation Index (NDVI) data, both from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. We estimated seasonal actual evapotranspiration (ETa) over a period of six years (2000-2005) for two major irrigated river basins in Afghanistan, the Kabul and the Helmand, by analyzing up to 19 cloud-free thermal and NDVI images from each year. These seasonal ETa estimates were used as relative indicators of year-to-year production magnitude differences. The temporal water- use pattern of the two irrigated basins was indicative of the cropping patterns specific to each region. Our results were comparable to field reports and to estimates based on watershed-wide crop water-balance model results. For example, both methods found that the 2003 seasonal ETa was the highest of all six years. The method also captured water management scenarios where a unique year-to-year variability was identified in addition to water-use differences between upstream and downstream basins. A major advantage of the energy-balance approach is that it can be used to quantify spatial extent of irrigated fields and their water-use dynamics without reference to source of water as opposed to a water- balance model which requires knowledge of both the magnitude and temporal distribution of rainfall and irrigation applied to fields.

Abstract: Target tracking is usually a challenging application for wireless sensor networks(WSNs) because it is always computation-intensive and requires real-time processing. Thispaper proposes a practical target tracking system based on the auto regressive movingaverage (ARMA) model in a distributed peer-to-peer (P2P) signal processing framework.In the proposed framework, wireless sensor nodes act as peers that perform target detection,feature extraction, classification and tracking, whereas target localization requires thecollaboration between wireless sensor nodes for improving the accuracy and robustness.For carrying out target tracking under the constraints imposed by the limited capabilities ofthe wireless sensor nodes, some practically feasible algorithms, such as the ARMA modeland the 2-D integer lifting wavelet transform, are adopted in single wireless sensor nodesdue to their outstanding performance and light computational burden. Furthermore, aprogressive multi-view localization algorithm is proposed in distributed P2P signalprocessing framework considering the tradeoff between the accuracy and energyconsumption. Finally, a real world target tracking experiment is illustrated. Results fromexperimental implementations have demonstrated that the proposed target tracking systembased on a distributed P2P signal processing framework can make efficient use of scarceenergy and communication resources and achieve target tracking successfully.